双馈感应风力发电机组鲁棒自适应协同镇定控制研究
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摘要
研究双馈感应风力发电机组在既有外部干扰又有结构参数不确定的情况下,基于Hamilton函数的自适应H_∞协同镇定问题,使多机闭环系统能够全局稳定且输出同步。考虑双馈风电机组的非线性本质,建立双馈风电机组的Hamilton模型,采用预反馈将其表示为耗散Hamilton系统,再考虑既有外部干扰又有结构参数不确定的情况,设计一种输出反馈+自适应干扰抑制的多机同步控制器,使得风电机组非线性系统能够保持协同运行。该控制器不仅对发电机组非线性系统的参数摄动具有较强的自适应能力,而且对外部扰动具有很强的抑制能力。两机风电机组的仿真结果验证了控制器的有效性。
The H_∞ adaptive collaborative stabilization of a doubly fed induction generator(DFIG) was studied based on the Hamilton function, when there were external disturbances and parameter uncertainties, in order to realize the closed-loop global stability and output synchronization of the multi machine system. The nonlinear nature of the doubly-fed wind power generator was considered, the Hamilton model for the DFIG was built, and expressed as a dissipative Hamilton system by pre-feedback. Then, the external disturbances and parameter uncertainties were considered, and a controller performing the output feedback and synchronous adaptive interference suppression was designed, so that the wind generator units can keep synchronous running. The controller has the strong adaptive ability not only for the parameter perturbation of the nonlinear wind generator unit, but also for the restraint of the external disturbance. The effectiveness of the controller was tested by the simulations of two wind generator units.
The H_∞ adaptive collaborative stabilization of a doubly fed induction generator(DFIG) was studied based on the Hamilton function, when there were external disturbances and parameter uncertainties, in order to realize the closed-loop global stability and output synchronization of the multi machine system. The nonlinear nature of the doubly-fed wind power generator was considered, the Hamilton model for the DFIG was built, and expressed as a dissipative Hamilton system by pre-feedback. Then, the external disturbances and parameter uncertainties were considered, and a controller performing the output feedback and synchronous adaptive interference suppression was designed, so that the wind generator units can keep synchronous running. The controller has the strong adaptive ability not only for the parameter perturbation of the nonlinear wind generator unit, but also for the restraint of the external disturbance. The effectiveness of the controller was tested by the simulations of two wind generator units.
引文
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[20]王玉振.广义Hamilton控制系统理论:实现,控制与应用[M].北京:科学出版社,2007.
[21]VAN DER SCHAFT A.L2-gain and passivity techniques in nonlinear control[M].New York:Springer Science&Business Media,2012.
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[2]BOUKHEZZAR B,SIGUERDIDJANE H.Nonlinear control with wind estimation of a DFIG variable speed wind turbine for power capture optimization[J].Energy Conversion and Management,2009,50(4):885-892.
[3]ODGAARD P F,STOUSTRUP J,KINNAERT M.Fault tolerant control of wind turbines-a benchmark model[J].IFAC Proceedings Volumes,2009,42(8):155-160.
[4]周志超,王成山,郭力,等.变速变桨距风电机组的全风速限功率优化控制[J].中国电机工程学报,2015,35(8):1837-1844.ZHOU Zhichao,WANG Chengshan,GOU Li,et al.Output power curtailment control of variable-speed variable-pitch wind turbine generator at all wind speed regions[J].Proceedings of the CSEE,2015,35(8):1837-1844.
[5]刘细平,林鹤云.风力发电机及风力发电控制技术综述[J].大电机技术,2007(3):17-20.LIU Xiping,LIN Heyun.Overview of wind power generators and the control technologies[J].Large Motor Technology,2007(3):17-20.
[6]吴忠强,谢建平.风力发电机自适应鲁棒保性能控制器设计[J].振动与冲击,2013,32(15):95-99.WU Zhongqiang,XIE Jianping.Adaptive guaranteed cost controller design for wind turbine[J].Journal of Vibration and Shock,2013,32(15):95-99.
[7]刘展,贾利民,庞宇.基于TMD的风力发电机组降载设计方法[J].振动与冲击,2017,36(3):196-201.LIU Zhan,JIA Limin,PANG Yu.Design method of wind turbine load shedding based on TMD[J].Journal of Vibration and Shock,2017,36(3):196-201.
[8]罗勇水,周民强,陈棋,等.兆瓦级风力发电机组传动系统动态特性研究[J].振动与冲击,2015,34(21):113-118.LUO Yongshui,ZHOU Minqiang,CHEN Qi,et al.Dynamic characteristics of a MW class wind turbine drive system[J].Journal of Vibration and Shock,2015,34(21):113-118.
[9]王晓,谢振宇,周红凯.磁悬浮风力发电机零偏置电流控制策略研究[J].振动与冲击,2014,33(23):63-67.XANG Xiao,XIE Zhenyu,ZHOU Hongkai.Control strategy with zero-bias current for magnetic levitation wind power generator[J].Journal of Vibration and Shock,2014,33(23):63-67.
[10]WU F,ZHANG X P,JU P,et al.Decentralized nonlinear control of wind turbine with doubly fed induction generator[J].IEEE Transactions on Power Systems,2008,23(2):613-621.
[11]姚骏,廖勇.基于全模糊控制器的交流励磁发电机励磁控制系统研究[J].中国电机工程学报,2007,27(33):36-41.YAO Jun,LIAO Yong,Research of AC excited generator excitation control system based on full fuzzy controller[J].Proceedings of the CSEE,2007,27(33):36-41.
[12]HAQUE M E,NEGNEVITSKY M,MUTTAQI K M.A novel control strategy for a variable-speed wind turbine with a permanent-magnet synchronous generator[J].IEEETransactions on Industry Applications,2010,46(1):331-339.
[13]王成亮,王宏华,向昌明,等.发电机进相能力的RBF神经网络模型[J].电工技术学报,2012,27(1):124-129.WANG Chengliang,WANG Honghua,XIANG Changming,et al.Generator leading phase ability model based on RBFneural network[J].Transactions of China Electrotechnical Society,2012,27(1):124-129.
[14]杨苹,周少雄,胡斌,等.双馈风力发电机系统的自抗扰神经网络的励磁控制[J].控制理论与应用,2012,29(2):251-256.YANG Ping,ZHOU Shaoxiong,HU Bin,et al.Active disturbance-rejection neural networks excitation-control of double-fed induction generator[J].Control Theory&Applications,2012,29(2):251-256.
[15]高勇,张文娟,杨媛,等.基于无源性的变速恒频双馈风力发电机控制系统[J].电工技术学报,2010,25(7):130-136.GAO Yong,ZHANG Wenjuan,YANG Yuan,et al.Passivity-based control system for VSCF doubly fed wind power generator[J].Transactions of China Electrotechnical Society,2010,25(7):130-136.
[16]WANG B,QIAN Y,WANG H.Multi-machine controller design of permanent magnet wind generators using Hamiltonian energy method[J].TELKOMNIKA Indonesian Journal of Electrical Engineering,2013,11(7):3750-3758.
[17]王冰,窦玉,王宏华.海上风电场双馈风电机群分布式协同控制研究[J].中国电机工程学报,2016(19):5279-5287.WANG Bing,DOU Yu,WANG Honghua.Distributed cooperative control research of doubly fed wind turbine groups in offshore wind farms[J].Proceedings of the CSEE,2016(19):5279-5287.
[18]任丽娜.永磁同步风力发电机的最佳功率跟踪控制策略研究[D].秦皇岛:燕山大学,2012.
[19]王冰,袁越.非线性无源控制理论及其在风力发电机组中的应用[M].北京:科学出版社,2015.
[20]王玉振.广义Hamilton控制系统理论:实现,控制与应用[M].北京:科学出版社,2007.
[21]VAN DER SCHAFT A.L2-gain and passivity techniques in nonlinear control[M].New York:Springer Science&Business Media,2012.
[22]LI C S,WANG Y Z.Protocol design for output consensus of port-controlled Hamiltonian multi-agent systems[J].Acta Automatica Sinica,2014,40(3):415-422.